We build world models that simulate manipulation scenes faithfully enough to validate, and one day, train policies without touching a robot. You'll develop generative models that make this work, with the controllability and physical fidelity to match real-robot behavior.
**What you'll do:**
* **Train video and dynamics models:** Develop world models with action conditioning for manipulation policies.
* **Push long-horizon coherence:** Develop architectures and training methods that extend rollout quality on hard physical tasks.
* **Own training infrastructure:** Run multi-GPU clusters, write custom CUDA, debug at scale.
* **Build the world-model data engine:** Design, implement, and improve a data engine that allows the world model to compound learning across customers and manipulation tasks.
**Requirements:**
* Very strong coding in Python and PyTorch (or similar).
* **Video generation experience:** Deep experience training image or video generation models end-to-end.
* **Large-scale training:** Track record operating training runs at cluster scale.
* **3D vision:** Working knowledge of multi-view geometry, scene reconstruction, and physical priors.
Visa sponsorship is offered for this role.
